Daily Endocrinology Research Analysis
Three impactful endocrinology studies stand out today. A population-based cohort links a subclinical primary aldosteronism phenotype to higher major adverse cardiovascular events independent of blood pressure. A randomized crossover trial in type 1 diabetes shows dapagliflozin elevates ketone bodies without altering GLP-1, glucagon, or somatostatin, underscoring euglycemic DKA risk. Genetic risk scores (GRS2), especially HLA class II components, predict progression across preclinical stages of t
Summary
Three impactful endocrinology studies stand out today. A population-based cohort links a subclinical primary aldosteronism phenotype to higher major adverse cardiovascular events independent of blood pressure. A randomized crossover trial in type 1 diabetes shows dapagliflozin elevates ketone bodies without altering GLP-1, glucagon, or somatostatin, underscoring euglycemic DKA risk. Genetic risk scores (GRS2), especially HLA class II components, predict progression across preclinical stages of type 1 diabetes.
Research Themes
- Subclinical primary aldosteronism and cardiovascular outcomes
- SGLT2 inhibitor safety in type 1 diabetes and ketogenesis
- Genetic risk stratification for preclinical type 1 diabetes progression
Selected Articles
1. Subclinical Primary Aldosteronism and Major Adverse Cardiovascular Events: A Longitudinal Population-Based Cohort Study.
In a population-based cohort of 2017 adults followed for a median 10.8 years, lower renin and higher aldosterone-to-renin ratio (ARR) were independently associated with increased MACE risk, whereas aldosterone alone was not. Outcome-derived thresholds (renin ≤4.0 ng/L; ARR ≥70 pmol/L per ng/L) discriminated higher risk, independent of blood pressure.
Impact: This study links a prevalent subclinical endocrine phenotype to hard cardiovascular outcomes beyond blood pressure, proposing actionable biochemical thresholds for risk stratification.
Clinical Implications: Consider screening for subclinical PA using renin and ARR in patients at cardiometabolic risk, even with controlled blood pressure. Thresholds (renin ≤4.0 ng/L; ARR ≥70 pmol/L per ng/L) may guide referrals for confirmatory testing and targeted therapy.
Key Findings
- Lower renin concentration and higher aldosterone-to-renin ratio were independently associated with higher MACE risk over 10.8 years.
- No significant association was found for aldosterone concentration alone with MACE.
- Outcome-derived thresholds (renin ≤4.0 ng/L; ARR ≥70 pmol/L per ng/L) doubled MACE risk, independent of blood pressure.
- The renin–MACE relationship was nonlinear, emphasizing low-renin risk.
Methodological Strengths
- Population-based prospective cohort with long-term follow-up (median 10.8 years).
- Measured baseline aldosterone and renin with multivariable and nonlinear Cox models, and outcome-derived thresholds.
- Administrative data linkage ensured robust outcome ascertainment.
Limitations
- Relatively few MACE events (n=57) may limit precision.
- Single baseline hormone measurement; potential residual confounding.
- Generalizability beyond the Québec population requires validation.
Future Directions: Prospective interventional studies to test whether early identification and targeted PA therapy in low-renin/high-ARR individuals reduces MACE.
2. CagriSema drives weight loss in rats by reducing energy intake and preserving energy expenditure.
In rats, CagriSema produced 12% weight loss with a 39% reduction in food intake, yet pair-feeding did not match this effect, indicating preservation of energy expenditure. Roughly one-third of the weight loss arose from blunting metabolic adaptation, suggesting a distinct mechanistic advantage over appetite suppression alone.
Impact: Identifies a mechanistic basis—blunting metabolic adaptation—for the superior weight loss efficacy of a dual amylin–GLP-1 approach, informing next-generation anti-obesity therapies.
Clinical Implications: If translatable to humans, therapies that combine appetite suppression with preservation of energy expenditure may sustain weight loss and reduce metabolic adaptation, guiding drug selection and combination strategies.
Key Findings
- CagriSema induced 12% weight loss in rats with a 39% reduction in energy intake.
- Pair-feeding did not recapitulate weight loss; weight matching required a 51% intake reduction.
- Approximately one-third of CagriSema's weight loss was attributable to preserved energy expenditure (blunted metabolic adaptation).
Methodological Strengths
- Careful partitioning of energy intake vs expenditure effects via pair-feeding and weight-matching comparators.
- Quantitative energy balance analysis enabling attribution to metabolic adaptation.
Limitations
- Preclinical rat model; translatability to humans remains to be established.
- Short- to mid-term assessments without long-term safety outcomes.
Future Directions: Human studies to quantify energy expenditure preservation with CagriSema or similar combinations, and to assess long-term weight maintenance and cardiometabolic outcomes.
3. Dapagliflozin's impact on hormonal regulation and ketogenesis in type 1 diabetes: a randomised controlled crossover trial.
In 13 adults with type 1 diabetes, short-term dapagliflozin increased plasma ketone bodies during hyperinsulinaemic euglycaemic clamps and oral glucose plus insulin tests, without altering GLP-1, glucagon, or somatostatin. These data highlight increased ketogenesis as a mechanism of heightened euglycaemic DKA risk under SGLT2 inhibitor add-on therapy.
Impact: Provides mechanistic human evidence that SGLT2 inhibition increases ketogenesis in type 1 diabetes independent of islet hormone changes, directly informing safety considerations.
Clinical Implications: When considering SGLT2 inhibitors off-label in type 1 diabetes, reinforce ketone monitoring and sick-day rules; hormone profiles may not signal impending ketosis. Risk mitigation strategies should focus on ketogenesis.
Key Findings
- Dapagliflozin increased plasma ketone bodies in both hyperinsulinaemic euglycaemic clamp and oral glucose plus insulin conditions (p<0.001).
- GLP-1, glucagon, and somatostatin concentrations were not significantly different between dapagliflozin and placebo.
- Findings suggest elevated ketogenesis without counter-regulatory hormone changes, aligning with euglycaemic DKA risk.
Methodological Strengths
- Randomised, placebo-controlled, crossover design increases internal validity.
- Use of gold-standard hyperinsulinaemic euglycaemic clamp and controlled OGTTC assessments.
Limitations
- Small sample size (n=13) limits generalisability and power.
- Open-label design and short-term intervention; no clinical outcome data.
Future Directions: Larger, blinded trials to quantify ketone dynamics and evaluate risk mitigation strategies (e.g., ketone monitoring protocols) in T1D using SGLT2 inhibitors.
4. Genetic Risk and Transition through Preclinical Stages of Type 1 Diabetes.
Across 4,314/3,066/2,045 participants for successive preclinical transitions, T1D GRS2 predicted all three stage transitions (HR 1.05–1.13 per unit), with HLA class II as the dominant driver. DR4 associated with early and late transitions; DR3 only with late (stage 2→3) progression.
Impact: Clarifies how aggregate genetic risk—especially HLA class II—shapes progression across preclinical stages, supporting incorporation of GRS2 into risk stratification.
Clinical Implications: Genetic risk scoring (GRS2) could refine monitoring intensity and enrollment in prevention trials by identifying individuals at higher risk of stage progression.
Key Findings
- T1D GRS2 was associated with all three preclinical stage transitions (HR 1.11, 1.05, and 1.13).
- HLA class II components drove associations across all transitions; HLA class I and DR4 associated with early and late transitions.
- DR3 associated only with the stage 2 to clinical T1D transition.
Methodological Strengths
- Large, well-phenotyped TrialNet cohorts with stage-specific transition analyses.
- Comprehensive genetic profiling (GRS2 with HLA/non-HLA dissection) and time-to-event modeling.
Limitations
- Effect sizes per unit GRS are modest; clinical thresholds need calibration.
- Follow-up durations not detailed; external validation needed for diverse populations.
Future Directions: Prospective validation of GRS2-integrated staging algorithms and testing whether GRS-informed monitoring/prevention strategies alter clinical onset.